Vice President, Data Architecture and Governance

## Exceed the expectations of our residential mortgage borrowers & business partners through superior service, simple processes, and effective communications.## We deliver on this mission by empowering our employees by encouraging and recognizing superior performance and innovative solutions, by promoting teamwork and divisional cooperation.
** POSITION SUMMARY
** The VP Data Architecture & Governance will serve as the visionary leader on data architecture, and governance across the mortgage origination, servicing, and secondary markets businesses. Reporting to the Chief Data Officer, this leader will define and lead the modernization of the company’s data ecosystem, transforming it into a secure, scalable, and trusted foundation for analytics, regulatory compliance, and AI-driven decisioning.

This individual is someone who can architect and build scalable, governed, and insight-ready data ecosystems from the ground up. You’ll be the technical authority behind our data architecture, working directly with engineers, modelers, and business leaders to ensure our data is trusted, connected, and driving real business value.
** DESCRIPTION
* *** Essential Functions, Duties, and Responsibilities**
* ** Strategic Leadership
*** Develop and execute a multi-year enterprise data governance strategy aligned with business objectives across originations, servicing, capital markets, and risk functions.
* Partner with business and technology executives to establish a unified data vision enabling operational efficiency, customer personalization, and advanced analytics.
* Chair the Enterprise Data Governance Council and drive executive alignment on policies, standards, and data-related investments.
* ** Data Architecture
*** Lead the design of an enterprise-wide data architecture standards and blueprint supporting master data, metadata management, reference data, and event-driven integration.
* Modernize legacy data systems by transitioning from on-premises monoliths to cloud-based data platforms (e.g., Azure, AWS, GCP) using lakehouse or data mesh/fabric principles.
* Enable real-time and batch data pipelines across origination, servicing, and collections systems using technologies like Kafka and Snowflake.
* Design and document end-to-end Data Lineage from source systems to business reporting to build integrated data flows across ingestion, processing, storage, and consumption layers
* Lead the design and evolution of enterprise data models
* ** Data Governance and Compliance
*** Establish enterprise data governance policies to ensure compliance with PCI, PII, PHI, GLBA, and GSE data standards.
* Apply modern methodologies like Agile, Domain-Driven Design (DDD), and Data Mesh
* Partner with security and privacy teams to ensure compliant data architecture
* Build a data stewardship model assigning clear data ownership and accountability across business units.
* Oversee enterprise data cataloging, classification, and retention practices to support audit readiness and regulatory examinations.
* Collaborate with Risk, Legal, and Compliance teams to ensure adherence to regulatory requirements
* ** Innovation and Enablement
*** Drive the adoption of AI-ready data architecture supporting predictive analytics, customer insights, and fraud/risk detection.
* Promote data literacy and self-service analytics across the enterprise through tools, training, and cultural change.
* Evaluate emerging technologies and vendor solutions to continuously evolve the data architecture landscape.
* Ability to effectively and accurately convey information to others.
* Performs related duties as assigned by management.
** Qualifications and Education Requirements
*** Bachelor’s degree in Computer Science, Engineering, or related field; master’s degree preferred.
* 12+ years of progressive experience in data architecture, governance, and analytics, with at least 5 years in senior leadership roles in large enterprise.
* Proven track record modernizing enterprise data platforms in regulated financial institutions.
* Strong understanding of data modeling, metadata management, data quality, lineage, and master data management (MDM).
* Experience with leading cloud data…